Search

A novel type of nonlinear robust control strategy is proposed in view of uncertain nonlinear factors, such as hysteresis, creep, and high-frequency vibration, of piezoelectric actuators (PEAs). This strategy can be used for the precise trajectory tracking of PEAs. The Bouc–Wen dynamic model is reasonably simplified to facilitate engineering application. The hysteresis term is summarized as an unknown term to avoid its nonlinear parameter identification. The controller robustness is achieved due to the nonsingular terminal sliding mode control, and the online estimation of unknown disturbances is realized because of the delay estimation technology; thus, no prior knowledge of the unknown boundary of the system is required. The precision robust differentiator is used to estimate the speed and acceleration signals in real time on the basis of the obtained displacement signals. The closed-loop stability of the system is proved by the Lyapunov criterion. Experimental results show that the proposed control strategy performs better than the traditional time-delay estimation control in terms of control accuracy and energy conservation. Therefore, the proposed control strategy can play an important role in the micro/nanofield driven by PEAs.

This paper presents a novel control strategy to compensate hysteretic nonlinearity and achieve precise positioning control of a cell puncture mechanism driven by a piezoelectric actuator (PEA). A dynamic model of the cell puncture mechanism is developed based on the Bouc–Wen model. Parameters of the nonlinear model are identified by particle swarm optimization. The strategy of feedforward (FF) control and sliding mode feedback (FB) control based on the Bouc–Wen inverse model is further developed to position the cell puncture mechanism. Zebrafish embryo is used as the validation object, wherein a cell micropuncture experiment is successfully performed. Proportional-integral sliding mode FB control plus FF control has a simple structure and exhibits excellent performance. Thus, this method can be easily extended to other micro-or nanopositioning mechanisms based on PEAs and adopted in practical applications. [ABSTRACT FROM AUTHOR]

This study deals with the design of a cell puncture mechanism (CPM) driven by a piezoelectric actuator to complete the cell puncture process. Then, a novel robust controller is proposed to realize precise CPM motion control. For the convenience of engineering application, the complex nonlinear hysteresis effect and unmolded term in CPM are summed up as an unknown term. Then, a simplified dynamic model is developed. Moreover, a robust controller is constructed by synthesizing the sliding mode control (SMC) with a proportional–integral–differential (PID)-type manifold and radial basis function neural network (RBFNN). The closed-loop stability and finite-time convergence of this controller are proven by the Lyapunov theory. With the self-learning ability of RBFNN, online estimation and real-time compensation of the unknown term can be realized. Moreover, the gain of the robust term in the controller can be reduced. Furthermore, the PID-type manifold improves the transient response speed of the controller and reduces the steady-state error of the system. The advantages of the PID-type manifold and RBFNN complement each another, thereby ensuring the excellent control quality of the proposed controller. Computer simulation results show the feasibility of the proposed simplified model and the robustness of the controller. These results can help improve the intelligence of CPM, particularly when this mechanism buffers from a sophisticated unstructured engineering environment. [ABSTRACT FROM AUTHOR]